Methods for motion estimation are generally known in the art and are used in the field of processing motion pictures. Motion estimation is the process of determining motion vectors that describe the transformation from one 2D image to another; usually from adjacent frames in a video sequence. The motion vectors may relate to the whole image (global motion estimation) or specific parts, such as rectangular blocks, arbitrary shaped patches or even per pixel. The motion vectors may be represented by a translational model or many other models that can approximate the motion of a real video camera, such as a rotation and translation in all three dimensions and zoom.
Applying the motion vectors to an image to synthesize the transformation to the next image is called motion compensation. The combination of motion estimation and motion compensation is a key part of video compression as used by MPEG 1, 2 and 4 as well as many other video codex.
A further application for motion estimation is the field of interpolating an intermediate frame between two adjacent frames in a video sequence.
The method for finding motion vectors can be categorized in the pixel-based methods, also called direct methods, and feature-based methods, also called indirect methods. In the following, it is focused on the pixel-based methods, in particular the block-matching algorithm, which is also well known in the art. Generally, the block-matching algorithm is a way of locating matching blocks in a sequence of digital video frames for the purposes of motion estimation. In particular, the purpose of a block-matching algorithm is to find a matching block from a frame i in some other frame j, which may appear before or after i.
EP 0 634 873 A2, for example discloses a method to determine the motion vectors in small picture segments of a television picture using block-matching algorithms. A further document disclosing a method for motion estimation using block-matching is EP 0 895 423 A2.
Although the block-matching algorithms used in the past perform well, problems often arise when the picture (frame) comprises many areas with low contrast. In order to overcome this problem, so-called contrast enhancement methods have been used to increase the contrast of the picture for block-matching purposes. In the prior art, for example EP 0 634 873 A2, the contrast enhancement is applied to the picture before processing the respective blocks by the block-matching algorithm.
Although this combination of contrast enhancement and block-matching works properly, there is always a demand for a reduction of circuitry and hence for cost reduction.